Less Decoder is More Encoder: Geometric Representation Learning from Novel View Synthesis

Paper recorded by Signals 4 on 2026-10-02 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-02 on arXiv · recorded by Signals 4 on 2026-10-05

Category: cs.AI · 人工智能 · first seen 2026-10-05

Abstract

This paper examines the role of Novel View Synthesis (NVS) in geometric representation learning. In principle, NVS should reason about 3D scene structure, thereby enabling transferable multi-view geometric representations. Yet, existing encoder-based NVS methods yield poor representations. This is not because of a lack of supervisory signal, but rather due to inconspicuous architectural choices: \

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